If you're looking for a platform that offers built-in analytics and insights into user preference and prompt performance for generative AI applications, Props AI is an excellent option. It provides detailed insights into user behavior, tracks token usage and costs, and monitors application performance. With features like error and latency tracking, model routing, and usage-based billing, Props AI helps optimize resource usage and improve the user experience. It supports Python and JavaScript/TypeScript configurations and offers a range of pricing tiers, making it accessible for developers and companies at various scales.
Another robust platform is Athina, which offers a comprehensive suite for experimentation, measurement, and optimization of AI applications. It includes real-time monitoring, cost tracking, customizable alerts, and LLM Observability. Athina supports popular frameworks and provides flexible plans suitable for teams of all sizes, making it a valuable tool for accelerating the development process and ensuring reliable AI applications.
For those focused on performance monitoring and prompt engineering, Klu offers a platform to build, deploy, and optimize generative AI applications. It supports multiple large language models and features built-in analytics, custom model support, and fast iteration tools. Klu’s pricing plans cater to different needs, from individual developers to enterprise-level teams, helping improve the workflow of AI engineers and teams through efficient and secure tools.
Lastly, HoneyHive provides a mission-critical environment for AI evaluation, testing, and observability. It includes features like automated CI testing, production pipeline monitoring, dataset curation, and prompt management. HoneyHive supports over 100 models via integrations with popular GPU clouds and offers a free developer plan, making it accessible for individual developers and researchers. Its customizable enterprise plan includes advanced features for teams requiring comprehensive support.